Systematic detection of errors in genetic linkage data.

Genomics
Authors
Keywords
Abstract

Construction of dense genetic linkage maps is hampered, in practice, by the occurrence of laboratory typing errors. Even relatively low error rates cause substantial map expansion and interfere with the determination of correct genetic order. Here, we describe a systematic method for overcoming these difficulties, based on incorporating the possibility of error into the usual likelihood model for linkage analysis. Using this approach, it is possible to construct genetic maps allowing for error and to identify the typings most likely to be in error. The method has been implemented for F2 intercrosses between two inbred strains, a situation relevant to the construction of genetic maps in experimental organisms. Tests involving both simulated and real data are presented, showing that the method detects the vast majority of errors.

Year of Publication
1992
Journal
Genomics
Volume
14
Issue
3
Pages
604-10
Date Published
1992 Nov
ISSN
0888-7543
PubMed ID
1427888
Links
Grant list
P50HG00098 / HG / NHGRI NIH HHS / United States
R01HG00126 / HG / NHGRI NIH HHS / United States
R01HG00316 / HG / NHGRI NIH HHS / United States